Integrating Gene Expression Programming and Geographic Information Systems for Solving a Multi Site Land Use Allocation Problem

@Article{Eldrandaly:2009:AJAS,
title = "Integrating Gene Expression Programming and Geographic
Information Systems for Solving a Multi Site Land Use
Allocation Problem",
author = "Khalid A. Eldrandaly",
journal = "American Journal of Applied Sciences",
year = "2009",
volume = "6",
number = "5",
pages = "1021--1027",
keywords = "genetic algorithms, genetic programming, gene
expression programming, Multi site land use allocation,
GIS, SDSS",
publisher = "Science Publications",
ISSN = "1546-9239",
URL = "http://www.scipub.org/fulltext/ajas/ajas651021-1027.pdf",
URL = "http://thescipub.com/html/10.3844/ajassp.2009.1021.1027",
broken = "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=15469239\&date=2009\&volume=6\&issue=5\&spage=1021",
bibsource = "OAI-PMH server at www.doaj.org",
oai = "oai:doaj-articles:374b808b659956eb2527109ade485337",
DOI = "doi:10.3844/ajassp.2009.1021.1027",
size = "7 pages",
abstract = "Problem statement: Land use planning may be defined as
the process of allocating different activities or uses
to specific units of area within a region. Multi sites
Land Use Allocation Problems (MLUA) refer to the
problem of allocating more than one land use type in an
area. MLUA problem is one of the truly NP Complete
(combinatorial optimisation) problems. Approach: To
cope with this type of problems, intelligent techniques
such as genetic algorithms and simulated annealing,
have been used. In this study a new approach for
solving MLUA problems was proposed by integrating Gene
Expression Programming (GEP) and GIS. The feasibility
of the proposed approach in solving MLUA problems was
checked using a fictive case study. Results: The
results indicated clearly that the proposed approach
gives good and satisfactory results.
Conclusion/Recommendation: Integrating GIS and GEP is a
promising and efficient approach for solving MLUA
problems. This research focused on minimising the
development costs and maximising the compactness of the
allocated land use. The optimization model can be
extended in the future to maximize also the spatial
contiguity of the allocated land use.",
notes = "Faculty of Computers and Informatics, Zagazig
University, Egypt",
}